COVID-19

The effects of as a libido booster and sexual enhancer on the reproductive system of male rats.

BACKGROUND AND AIM: Alongside the advancement of various modern treatments, attention has recently been focused on finding alternative infertility treatments based on diet and herbal medicine. (wild pistachio; Baneh) is a plant species traditionally known as a libido booster and sexual enhancer.

Using different machine learning models to classify patients into mild and severe cases of COVID-19 based on multivariate blood testing.

COVID-19 is a serious respiratory disease. The ever-increasing number of cases is causing heavier loads on the health service system. Using 38 blood test indicators on the first day of admission for the 422 patients diagnosed with COVID-19 (from January 2020 to June 2021) to construct different machine learning (ML) models to classify patients into either mild or severe cases of COVID-19. All mode...

A comparative analysis of eleven neural networks architectures for small datasets of lung images of COVID-19 patients toward improved clinical decisions.

The 2019 novel severe acute respiratory syndrome coronavirus 2-SARS-CoV2, commonly known as COVID-19, is a highly infectious disease that has endanger...

eARDS: A multi-center validation of an interpretable machine learning algorithm of early onset Acute Respiratory Distress Syndrome (ARDS) among critically ill adults with COVID-19.

We present an interpretable machine learning algorithm called 'eARDS' for predicting ARDS in an ICU population comprising COVID-19 patients, up to 12-...

Multimodal deep learning models for the prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.

The achievement of the pathologic complete response (pCR) has been considered a metric for the success of neoadjuvant chemotherapy (NAC) and a powerfu...

Ten public health strategies to control the Covid-19 pandemic: the Saudi Experience.

Saudi Arabia plays an important strategic role within the Middle East and afar because of its geographical location, and being the host of one of the ...

Diagnostic Test Accuracy of Deep Learning Detection of COVID-19: A Systematic Review and Meta-Analysis.

RATIONALE AND OBJECTIVE: To perform a meta-analysis to compare the diagnostic test accuracy (DTA) of deep learning (DL) in detecting coronavirus disea...

Optimization in the Context of COVID-19 Prediction and Control: A Literature Review.

This paper presents an overview of some key results from a body of optimization studies that are specifically related to COVID-19, as reported in the ...

Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network.

Rare diseases affect millions of people worldwide, and discovering their genetic causes is challenging. More than half of the individuals analyzed by ...

Federated learning for predicting clinical outcomes in patients with COVID-19.

Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity,...

Are nucleos(t)ide analogues effective against severe outcomes in COVID-19 and hepatitis B virus coinfection?

BACKGROUND AND AIM: The impact of chronic hepatitis B virus (HBV) infection and nucleos(t)ide analogue (NUC) treatment on disease severity and clinica...

Quantitative particle agglutination assay for point-of-care testing using mobile holographic imaging and deep learning.

Particle agglutination assays are widely adopted immunological tests that are based on antigen-antibody interactions. Antibody-coated microscopic part...

Application of green synthesised copper iodide particles on cotton fabric-protective face mask material against COVID-19 pandemic.

Microorganisms cause variety of diseases that constitutes a severe threat to mankind. Due to the upsurge of many infectious diseases, there is a high ...

Automatic Assessment of Mitral Regurgitation Severity Using the Mask R-CNN Algorithm with Color Doppler Echocardiography Images.

Accurate assessment of mitral regurgitation (MR) severity is critical in clinical diagnosis and treatment. No single echocardiographic method has been...

Predictive model for progressive salinization in a coastal aquifer using artificial intelligence and hydrogeochemical techniques: a case study of the Nile Delta aquifer, Egypt.

To monitor groundwater salinization due to seawater intrusion (SWI) in the aquifer of the eastern Nile Delta, Egypt, we developed a predictive regress...

Automated machine learning for endemic active tuberculosis prediction from multiplex serological data.

Serological diagnosis of active tuberculosis (TB) is enhanced by detection of multiple antibodies due to variable immune responses among patients. Cli...

Diagnostic classification of coronavirus disease 2019 (COVID-19) and other pneumonias using radiomics features in CT chest images.

We propose a classification method using the radiomics features of CT chest images to identify patients with coronavirus disease 2019 (COVID-19) and o...

Deep learning models for benign and malign ocular tumor growth estimation.

Relatively abundant availability of medical imaging data has provided significant support in the development and testing of Neural Network based image...

ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation.

Regulatory elements control gene expression through transcription initiation (promoters) and by enhancing transcription at distant regions (enhancers)...

NanoCaller for accurate detection of SNPs and indels in difficult-to-map regions from long-read sequencing by haplotype-aware deep neural networks.

Long-read sequencing enables variant detection in genomic regions that are considered difficult-to-map by short-read sequencing. To fully exploit the ...